1. Field of the Invention
The present invention generally relates to the field of computer image processing of computer tomography (CT) data and, more particularly to the problem of restoring noise-corrupted boundaries in CT images, and to the characterizing and displaying of this restored boundary information.
2. Background Description
U.S. Pat. No. 5,416,815, which is incorporated herein by reference in its entirety, describes computer tomography (CT) systems and the method of image reconstruction from projections.
Computed tomography images are created from projection data by a process known as "image reconstruction from projections". If the projection data are corrupted by noise, the reconstructed images will in turn be corrupted by noise. The artifacts in the images resulting from this noise are known as "reconstruction artifacts".
For example, in X-ray CT imaging, a significant amount of noise can be introduced into the projection data when the objects being scanned contain metal. The reconstruction artifacts manifest in the form of blooming and streaking artifacts that radiate from he regions of the image where the metal is present.
These artifacts (known as "metal-induced" reconstruction artifacts) produce severe corruption especially at the boundaries of objects in the images. This significantly limits the clinical usefulness of the images, both for diagnostic and therapeutic purposes, since an accurate knowledge about locations of object boundaries is crucial in applications such as computer-assisted surgery, and radiotherapy.
There are two basic approaches to recover information about the corrupted boundaries, a "projection-based" approach, and an "image-based" approach.
In the "projection-based" approach, projection data obtained from the CT scanner are used to recover missing boundary information. The prior art in boundary recovery from projection data includes: m. Bergstrom, J. Litton, L. Eriksson, C. Bohm, and G. Blomqvist, "Determination of Object Contour from Projections for Attenuation Correction in Cranial-Positron Emission Tomography", Journal of Computer Assisted Tomography, April 1982, 6(2), pp. 365-372; Jean-Philippe Thirion and Nicholas Ayache, "Method and device for examining a body, particularly for tomography", U.S. Pat. No. 5,421,330, (1995); N. Srinivasa, K. R. Ramakrishnan, and K. Rajgopal, "Detection of edges from projections", IEEE Trans. Medical Imaging, March 1992, 11(1), pp.76-80; Ralph Benjamin, "Method and apparatus for generating images", U.S. Pat. No. 5,647,018, (1997).
In the "image-based" approach, the noisy CT image is first "cleaned-up" by applying a suitable noise-reduction algorithm. Since this process improves the overall quality of the image, it will improve the quality of the boundaries, which can then be determined with improved precision. Since the image-based methods are primarily concerned with improving the overall quality of the image, they are not especially well-suited for the specific task of boundary-recovery. Nevertheless, they are included here for the sake of completeness.
In general, the most appropriate noise reduction algorithms to use in the image-based approach are hose algorithms known as "metal artifact reduction" (MAR) methods. The prior art in MAR algorithms includes the following: D. D. Robertson, P. J. Weiss, E. K. Fishman, D. Magid, and P. S. Walker, "Evaluation of CT techniques for reducing artifacts in the presence of metallic orthopedic implants", Journal of Computer Assisted Tomography, March-April 1988, 12(2), pp. 236-41; Hamid Soltanian-Zadeh, Joe P. Windham, and Jalal Soltanianzadeh, "CT Artifact Correction: An Image Processing Approach", SPIE Medical Imaging '96, Newport Beach, Calif. February 1996; Heang K. Tuy, "An Algorithm to Reduce Clip Artifacts in CT Images", SPIE Vol. 1652 Medical Imaging VI: Image processing (1992); G. H. Glover and N. J. Pelc, "An algorithm for the reduction of metal clip artifacts in CT reconstruct ions", Medical Physics, 8(6), November/December 1981, pp. 799-807; T. Hinderling, P. Ruegsegger, M. Anliker, and C. Dietschi, "Computed Tomography reconstruction from hollow projections: an application to in vivo valuation of artificial hip joints", Journal of Computer Assisted Tomography, February 1979, 3(1), pp. 52-57; W. A. Kalender, R. Hebel, and J. Ebersberger, "Reduction of CT artifacts caused by metallic implants", Radiology, August 1987, 164(2), pp. 576-7; E. Klotz, W. A. Kalender, R. Sokiranski, and D. Felsenberg, "Algorithms for the reduction of CT artifacts caused by metallic implants", Medical Imaging IV: PACS System Design and Evaluation, vol. 1234, Newport Beach, Calif. February 1990, pp. 642-650; R. M. Lewitt and B. H. T. Bates, "Image reconstruction from projections: IV: Projection completion methods (computational examples)", Optik 50, 1978, pp. 269-278; B. E. Oppenheim, "Reconstruction tomography from incomplete projections", Reconstruction Tomography in Diagnostic and Nuclear Medicine, Ter-Pogossian (editor), University Park Press, Baltimore, 1977, pp. 155-183; and G. Wang, D. L. Snyder, A. O'Sullivan, and M. W. Vannier, "Iterative deblurring for CT metal artifact reduction", IEEE Trans. Medical Imaging, October 1996, 14(5), pp. 657-664.
The following are the limitations of the prior art. The existing projection-based boundary-recovery methods are designed to work with high-quality projection data, that is projection data that are (i) highly-sampled, (ii) of high-resolution, and (iii) contain an insignificant amount of noise. Unlike the present invention, they are not designed to handle noisy projection data, or sparsely-sampled or low-resolution projection data.
Therefore, these methods are not suitable for embodiment in practical, real-world systems that can be routinely used in hospitals and medical clinics, and that rely only on data that are readily available from standard medical CT scanners.
The image-based methods, as already mentioned, are not especially well-suited for the specific task of boundary-recovery. Since they are not expressly designed to solve this problem.